Field
Certain aspects of the present disclosure generally relate to neural system engineering and, more particularly, to systems and methods for blink and averted gaze avoidance in photographic images.
Background
An artificial neural network, which may comprise an interconnected group of artificial neurons (i.e., neuron models), is a computational device or represents a method to be performed by a computational device. Artificial neural networks may have corresponding structure and/or function in biological neural networks. Artificial neural networks, however, may provide innovative and useful computational techniques for certain applications in which traditional computational techniques are cumbersome, impractical, or inadequate. Because artificial neural networks can infer a function from observations, such networks are particularly useful in applications where the complexity of the task or data makes the design of the function by conventional techniques burdensome.
In some cases, a photograph may include a subject that is blinking and/or not looking at the camera. Accordingly, it is desirable to capture an image with each subject looking at the camera and also not blinking. Still, it may be difficult to capture a desired image when the image includes a large group of individuals, distracted individuals, young children, and/or individuals that may be actively avoiding the camera. Neural networking techniques may be employed to address these issues.